Stochastic agent-based modelling for reality
This D.Phil. thesis develops a new agent-based simulation model to improve the results of analysis, which solely uses discrete choice modelling, as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discret...
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| Format: | Thesis |
| Language: | English |
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2005
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| _version_ | 1817931793257463808 |
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| author | Takama, T |
| author2 | Preston, J |
| author_facet | Preston, J Takama, T |
| author_sort | Takama, T |
| collection | OXFORD |
| description | This D.Phil. thesis develops a new agent-based simulation model to improve the results of analysis, which solely uses discrete choice modelling, as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discrete choice analysis are well known. However, results with these conventional conventional approaches, which conduct analysis solely with discrete choice models, can be biased if interaction and learning effects are significant. The Minority Game, in which agents try to choose the option of the minority side, is an appropriate tool to deal with these problems. The situation in the Upper Derwent Valley can be explained with economic game theories and the Minority Game. The two approaches mutually help to analyse the situation in the Upper Derwent Valley leading to the development of a stochastic Minority Game. The stochastic Minority Game was tested with an online game (questionnaire), which was played 3,886 times by response in all around the world. The practical part of this thesis examines the components of the stochastic Minority Game with the data collected around the Upper Derwent Valley. The main data was collected using a stated preference survey. Overall, 700 questionnaires were distributed and 323 of them were returned (i.e. a return rate of 46.1 %). In the practical part, the agent-based model has four sub modules: 1) Multinomial mixed logit model for mode choice, 2) Binary logit model for parking location choice, 3) Markov queue model for parking network, and 4) the Minority Game for parking congestion and learning. This simulation model produces comprehensive outputs including mode choices, congestion levels, and user utilities. The results show that the road user charging scheme reduces car demand in the Upper Derwent Valley and ensures a reduction in congestion at the parking areas. The model also shows that an exemption will increase the utilities of elderly visitors without substantially sacrificing those of younger visitors. In conclusion, the simulation model demonstrated that oversimplification in conventional approaches solely using discrete choice models gave significant biases when real world problems were analysed. |
| first_indexed | 2024-03-06T18:25:03Z |
| format | Thesis |
| id | oxford-uuid:07a643ed-c98a-4e66-936b-e8b558dbc1e3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-12-09T03:27:40Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | oxford-uuid:07a643ed-c98a-4e66-936b-e8b558dbc1e32024-12-01T10:35:57ZStochastic agent-based modelling for realityThesishttp://purl.org/coar/resource_type/c_db06uuid:07a643ed-c98a-4e66-936b-e8b558dbc1e3EnvironmentGeographyEconomicsGeography & travelTransition economicsMicroeconomicsTransportDecision scienceEnglishOxford University Research Archive - Valet2005Takama, TPreston, JThis D.Phil. thesis develops a new agent-based simulation model to improve the results of analysis, which solely uses discrete choice modelling, as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discrete choice analysis are well known. However, results with these conventional conventional approaches, which conduct analysis solely with discrete choice models, can be biased if interaction and learning effects are significant. The Minority Game, in which agents try to choose the option of the minority side, is an appropriate tool to deal with these problems. The situation in the Upper Derwent Valley can be explained with economic game theories and the Minority Game. The two approaches mutually help to analyse the situation in the Upper Derwent Valley leading to the development of a stochastic Minority Game. The stochastic Minority Game was tested with an online game (questionnaire), which was played 3,886 times by response in all around the world. The practical part of this thesis examines the components of the stochastic Minority Game with the data collected around the Upper Derwent Valley. The main data was collected using a stated preference survey. Overall, 700 questionnaires were distributed and 323 of them were returned (i.e. a return rate of 46.1 %). In the practical part, the agent-based model has four sub modules: 1) Multinomial mixed logit model for mode choice, 2) Binary logit model for parking location choice, 3) Markov queue model for parking network, and 4) the Minority Game for parking congestion and learning. This simulation model produces comprehensive outputs including mode choices, congestion levels, and user utilities. The results show that the road user charging scheme reduces car demand in the Upper Derwent Valley and ensures a reduction in congestion at the parking areas. The model also shows that an exemption will increase the utilities of elderly visitors without substantially sacrificing those of younger visitors. In conclusion, the simulation model demonstrated that oversimplification in conventional approaches solely using discrete choice models gave significant biases when real world problems were analysed. |
| spellingShingle | Environment Geography Economics Geography & travel Transition economics Microeconomics Transport Decision science Takama, T Stochastic agent-based modelling for reality |
| title | Stochastic agent-based modelling for reality |
| title_full | Stochastic agent-based modelling for reality |
| title_fullStr | Stochastic agent-based modelling for reality |
| title_full_unstemmed | Stochastic agent-based modelling for reality |
| title_short | Stochastic agent-based modelling for reality |
| title_sort | stochastic agent based modelling for reality |
| topic | Environment Geography Economics Geography & travel Transition economics Microeconomics Transport Decision science |
| work_keys_str_mv | AT takamat stochasticagentbasedmodellingforreality |